Quarto notes

library(ggplot2)

Quarto root directory

If there’s not a Quarto project (which is not the same as an Rproject), i.e. the .qmds are standalone, then the above rmarkdown method works to set the root to the Rproject. But if there is a Quarto project (I’ve moved to almost always doing this), then we can set the Quarto root directory in the _quarto.yml for the project. There are actually two useful settings we can make there- a project-wide output directory, and what to use to execute. There are (to my knowledge) two options for execute-dir- execute-dir: file and execute-dir: project, which set the root for rendering as the file location or the project. It almost always makes most sense to use project, because then everything uses the same reference for relative paths. For this website, that yaml is


project:
  type: website
  output-dir: docs
  execute-dir: project

Linking pages

This is fairly specific to websites (and I guess books?). Sorted out in the website-specific page. Takehome is links need to be relative to the file. And so those in different directories often have to use ../other_dir/other_file.qmd to get up and over.

Nested Rprojects

The only exception that I’ve run into so far is a weird situation where I have a Quarto project with an Rproject in a subdirectory because I want the Quarto to have access to several different code projects. The catch is that if I use paths relative to the R project and ask Quarto to render, all the paths are wrong. They are also wrong if I Run or run the code cells interactively. If I add the Rmarkdown setup chunk above knitr::opts_knit$set(root.dir = rprojroot::find_rstudio_root_file()), then Run and interactive stuff works, but when I try to quarto render, it can’t find the Rproject because it’s looking at the same level and up, and the Rproj is in a directory down.

So, the workaround I’ve come up with is to set execute-dir: file, so the dir is set to the file dir, which is inside the Rproject. Then, use an Rmarkdown-style setup chunk with knitr::opts_knit$set(root.dir = rprojroot::find_rstudio_root_file()) to reset the directory to the Rproject root dir.

```{r setup}
knitr::opts_knit$set(root.dir = rprojroot::find_rstudio_root_file())
```

Then the code both Runs and renders, and we don’t have to keep track of paths relative to two different nested projects manually. This approach works if the internal projects are self-contained (and we often want them to be). But if we need to render something across several, we’ll need to do something different.

Other options that might work but I haven’t tried are parameterised notebooks (with conditional params?) Or using freeze and virtual environments (see docs)

What I really want is a way to set the execute-dir on a file-by-file basis in the header yaml, but that doesn’t seem to work.

Headers in VS code vs Rstudio

I had a few notebooks that ran fine in Rstudio, but wouldn’t render in VS (or from command line). I got the very cryptic error YAMLException: can not read a block mapping entry; a multiline key may not be an implicit key with a line and col number that didn’t seem to correspond to anything with YAML in the project- not the file header, not the _quarto.yml, not _quarto.yaml.local, and nothing particularly useful showed up on google.

The solution seems to be to add an explicit line for editor: visual in the file header, e.g.

title: Test
author: Galen Holt
format:
  html:
    df-print: paged
editor: visual

It doesn’t seem to matter if the title and author are wrapped in double-quotes (which was one suggestion online).

I think what’s happening is that Rstudio’s visual editor is adding some hidden formatting syntax that gets exposed and looks like YAML to VS and the quarto CLI.

Python paths

If we use {reticulate}, R wants to know where the python lives, and gets grumpy if it can’t find it. Sometimes it silently points somewhere we don’t want, and other times we see errors like

Error creating conda environment 'C:/Users/galen/Documents/Website/galen_website/renv/python/r-reticulate' [exit code 1]

Rprofile

The main solution is to edit .Rprofile to set the RETICULATE_PYTHON environment variable,

Sys.setenv(RETICULATE_PYTHON = '../werptoolkitpy/.venv/Scripts/python.exe')

Note that this can either be a full path, or relative to the R project directory- in the situation above, I have the R project nested in a Quarto project that also contains a py project, so we need to go up and over to get to the .venv.

This is needed to get any of the reticulate code to work (though you can set it on a file-by-file basis.

Additional issues can come up with Quarto though.

Quarto environment

When we run Quarto inside Rstudio in parallel with an R project, everything works fine. But, if Quarto is run through VScode, for some reason it doesn’t hit the .Rprofile and so doesn’t run the line we just added, and we’re back to using the wrong python and errors about conda. To make it more complex, Quarto has its own python environment variable QUARTO_PYTHON. This is all more complicated when the Quarto project directory doesn’t match the R project directory.

The solution is to set up a _environment file in the Quarto project directory to set those variables according to the docs (and maybe PY_PYTHON too, just to be safe- I can’t find the docs to know how these differ). For my case, my _environment file looks like

RETICULATE_PYTHON='../werptoolkitpy/.venv/Scripts/python.exe'
QUARTO_PYTHON='werptoolkitpy/.venv/Scripts/python.exe'
PY_PYTHON='werptoolkitpy/.venv/Scripts/python.exe'

Here, again, I have Rproject nested in Quarto proj, but they access this file differently so the paths differ even though they point to the same place. RETICULATE_PYTHON needs to get up and out of the R subdir and over to the py side of things, while the Quarto project is the outer dir and so QUARTO_PYTHON can go straight in to the py subdir.

As far as I can tell, this does NOT supersede the necessity of setting .Rprofile, which is needed for the R code to run. This stuff in _environment is in addition so Quarto (especially in VS) can access the right info.

Table printing

Style

Use the yaml header to declare style, one of paged, kable, tibble, and default as in documentation. In a twist, default seems to be the way to do some customisation using S3, see https://debruine.github.io/quarto_demo/table.html, though I haven’t played with that.

So, typically the yaml header would be something like

format:
  html:
    df-print: paged

Can I change that for a single chunk? Work on that later. Putting it in as #| df-print: option isn’t recognized.

Row number

The different df-print options have different defaults of how much they print (and with paged it doesn’t matter so much). As far as I can tell, tibble prints the whole thing, and kable prints 10 rows. Sometimes we want to control that though - maybe we have a df with 13 rows, and we want to just print the whole thing.

The default is 10, though that’s not working when I render to the web for some reason

```{r}
iris
```
Sepal.Length Sepal.Width Petal.Length Petal.Width Species
5.1 3.5 1.4 0.2 setosa
4.9 3.0 1.4 0.2 setosa
4.7 3.2 1.3 0.2 setosa
4.6 3.1 1.5 0.2 setosa
5.0 3.6 1.4 0.2 setosa
5.4 3.9 1.7 0.4 setosa
4.6 3.4 1.4 0.3 setosa
5.0 3.4 1.5 0.2 setosa
4.4 2.9 1.4 0.2 setosa
4.9 3.1 1.5 0.1 setosa
5.4 3.7 1.5 0.2 setosa
4.8 3.4 1.6 0.2 setosa
4.8 3.0 1.4 0.1 setosa
4.3 3.0 1.1 0.1 setosa
5.8 4.0 1.2 0.2 setosa
5.7 4.4 1.5 0.4 setosa
5.4 3.9 1.3 0.4 setosa
5.1 3.5 1.4 0.3 setosa
5.7 3.8 1.7 0.3 setosa
5.1 3.8 1.5 0.3 setosa
5.4 3.4 1.7 0.2 setosa
5.1 3.7 1.5 0.4 setosa
4.6 3.6 1.0 0.2 setosa
5.1 3.3 1.7 0.5 setosa
4.8 3.4 1.9 0.2 setosa
5.0 3.0 1.6 0.2 setosa
5.0 3.4 1.6 0.4 setosa
5.2 3.5 1.5 0.2 setosa
5.2 3.4 1.4 0.2 setosa
4.7 3.2 1.6 0.2 setosa
4.8 3.1 1.6 0.2 setosa
5.4 3.4 1.5 0.4 setosa
5.2 4.1 1.5 0.1 setosa
5.5 4.2 1.4 0.2 setosa
4.9 3.1 1.5 0.2 setosa
5.0 3.2 1.2 0.2 setosa
5.5 3.5 1.3 0.2 setosa
4.9 3.6 1.4 0.1 setosa
4.4 3.0 1.3 0.2 setosa
5.1 3.4 1.5 0.2 setosa
5.0 3.5 1.3 0.3 setosa
4.5 2.3 1.3 0.3 setosa
4.4 3.2 1.3 0.2 setosa
5.0 3.5 1.6 0.6 setosa
5.1 3.8 1.9 0.4 setosa
4.8 3.0 1.4 0.3 setosa
5.1 3.8 1.6 0.2 setosa
4.6 3.2 1.4 0.2 setosa
5.3 3.7 1.5 0.2 setosa
5.0 3.3 1.4 0.2 setosa
7.0 3.2 4.7 1.4 versicolor
6.4 3.2 4.5 1.5 versicolor
6.9 3.1 4.9 1.5 versicolor
5.5 2.3 4.0 1.3 versicolor
6.5 2.8 4.6 1.5 versicolor
5.7 2.8 4.5 1.3 versicolor
6.3 3.3 4.7 1.6 versicolor
4.9 2.4 3.3 1.0 versicolor
6.6 2.9 4.6 1.3 versicolor
5.2 2.7 3.9 1.4 versicolor
5.0 2.0 3.5 1.0 versicolor
5.9 3.0 4.2 1.5 versicolor
6.0 2.2 4.0 1.0 versicolor
6.1 2.9 4.7 1.4 versicolor
5.6 2.9 3.6 1.3 versicolor
6.7 3.1 4.4 1.4 versicolor
5.6 3.0 4.5 1.5 versicolor
5.8 2.7 4.1 1.0 versicolor
6.2 2.2 4.5 1.5 versicolor
5.6 2.5 3.9 1.1 versicolor
5.9 3.2 4.8 1.8 versicolor
6.1 2.8 4.0 1.3 versicolor
6.3 2.5 4.9 1.5 versicolor
6.1 2.8 4.7 1.2 versicolor
6.4 2.9 4.3 1.3 versicolor
6.6 3.0 4.4 1.4 versicolor
6.8 2.8 4.8 1.4 versicolor
6.7 3.0 5.0 1.7 versicolor
6.0 2.9 4.5 1.5 versicolor
5.7 2.6 3.5 1.0 versicolor
5.5 2.4 3.8 1.1 versicolor
5.5 2.4 3.7 1.0 versicolor
5.8 2.7 3.9 1.2 versicolor
6.0 2.7 5.1 1.6 versicolor
5.4 3.0 4.5 1.5 versicolor
6.0 3.4 4.5 1.6 versicolor
6.7 3.1 4.7 1.5 versicolor
6.3 2.3 4.4 1.3 versicolor
5.6 3.0 4.1 1.3 versicolor
5.5 2.5 4.0 1.3 versicolor
5.5 2.6 4.4 1.2 versicolor
6.1 3.0 4.6 1.4 versicolor
5.8 2.6 4.0 1.2 versicolor
5.0 2.3 3.3 1.0 versicolor
5.6 2.7 4.2 1.3 versicolor
5.7 3.0 4.2 1.2 versicolor
5.7 2.9 4.2 1.3 versicolor
6.2 2.9 4.3 1.3 versicolor
5.1 2.5 3.0 1.1 versicolor
5.7 2.8 4.1 1.3 versicolor
6.3 3.3 6.0 2.5 virginica
5.8 2.7 5.1 1.9 virginica
7.1 3.0 5.9 2.1 virginica
6.3 2.9 5.6 1.8 virginica
6.5 3.0 5.8 2.2 virginica
7.6 3.0 6.6 2.1 virginica
4.9 2.5 4.5 1.7 virginica
7.3 2.9 6.3 1.8 virginica
6.7 2.5 5.8 1.8 virginica
7.2 3.6 6.1 2.5 virginica
6.5 3.2 5.1 2.0 virginica
6.4 2.7 5.3 1.9 virginica
6.8 3.0 5.5 2.1 virginica
5.7 2.5 5.0 2.0 virginica
5.8 2.8 5.1 2.4 virginica
6.4 3.2 5.3 2.3 virginica
6.5 3.0 5.5 1.8 virginica
7.7 3.8 6.7 2.2 virginica
7.7 2.6 6.9 2.3 virginica
6.0 2.2 5.0 1.5 virginica
6.9 3.2 5.7 2.3 virginica
5.6 2.8 4.9 2.0 virginica
7.7 2.8 6.7 2.0 virginica
6.3 2.7 4.9 1.8 virginica
6.7 3.3 5.7 2.1 virginica
7.2 3.2 6.0 1.8 virginica
6.2 2.8 4.8 1.8 virginica
6.1 3.0 4.9 1.8 virginica
6.4 2.8 5.6 2.1 virginica
7.2 3.0 5.8 1.6 virginica
7.4 2.8 6.1 1.9 virginica
7.9 3.8 6.4 2.0 virginica
6.4 2.8 5.6 2.2 virginica
6.3 2.8 5.1 1.5 virginica
6.1 2.6 5.6 1.4 virginica
7.7 3.0 6.1 2.3 virginica
6.3 3.4 5.6 2.4 virginica
6.4 3.1 5.5 1.8 virginica
6.0 3.0 4.8 1.8 virginica
6.9 3.1 5.4 2.1 virginica
6.7 3.1 5.6 2.4 virginica
6.9 3.1 5.1 2.3 virginica
5.8 2.7 5.1 1.9 virginica
6.8 3.2 5.9 2.3 virginica
6.7 3.3 5.7 2.5 virginica
6.7 3.0 5.2 2.3 virginica
6.3 2.5 5.0 1.9 virginica
6.5 3.0 5.2 2.0 virginica
6.2 3.4 5.4 2.3 virginica
5.9 3.0 5.1 1.8 virginica

To print more rows, we can use the rows.print option. NOTE- this used to work, and now does not. Will need to sort out a new solution.

```{r}
#| rows.print: 15

iris
```
Sepal.Length Sepal.Width Petal.Length Petal.Width Species
5.1 3.5 1.4 0.2 setosa
4.9 3.0 1.4 0.2 setosa
4.7 3.2 1.3 0.2 setosa
4.6 3.1 1.5 0.2 setosa
5.0 3.6 1.4 0.2 setosa
5.4 3.9 1.7 0.4 setosa
4.6 3.4 1.4 0.3 setosa
5.0 3.4 1.5 0.2 setosa
4.4 2.9 1.4 0.2 setosa
4.9 3.1 1.5 0.1 setosa
5.4 3.7 1.5 0.2 setosa
4.8 3.4 1.6 0.2 setosa
4.8 3.0 1.4 0.1 setosa
4.3 3.0 1.1 0.1 setosa
5.8 4.0 1.2 0.2 setosa
5.7 4.4 1.5 0.4 setosa
5.4 3.9 1.3 0.4 setosa
5.1 3.5 1.4 0.3 setosa
5.7 3.8 1.7 0.3 setosa
5.1 3.8 1.5 0.3 setosa
5.4 3.4 1.7 0.2 setosa
5.1 3.7 1.5 0.4 setosa
4.6 3.6 1.0 0.2 setosa
5.1 3.3 1.7 0.5 setosa
4.8 3.4 1.9 0.2 setosa
5.0 3.0 1.6 0.2 setosa
5.0 3.4 1.6 0.4 setosa
5.2 3.5 1.5 0.2 setosa
5.2 3.4 1.4 0.2 setosa
4.7 3.2 1.6 0.2 setosa
4.8 3.1 1.6 0.2 setosa
5.4 3.4 1.5 0.4 setosa
5.2 4.1 1.5 0.1 setosa
5.5 4.2 1.4 0.2 setosa
4.9 3.1 1.5 0.2 setosa
5.0 3.2 1.2 0.2 setosa
5.5 3.5 1.3 0.2 setosa
4.9 3.6 1.4 0.1 setosa
4.4 3.0 1.3 0.2 setosa
5.1 3.4 1.5 0.2 setosa
5.0 3.5 1.3 0.3 setosa
4.5 2.3 1.3 0.3 setosa
4.4 3.2 1.3 0.2 setosa
5.0 3.5 1.6 0.6 setosa
5.1 3.8 1.9 0.4 setosa
4.8 3.0 1.4 0.3 setosa
5.1 3.8 1.6 0.2 setosa
4.6 3.2 1.4 0.2 setosa
5.3 3.7 1.5 0.2 setosa
5.0 3.3 1.4 0.2 setosa
7.0 3.2 4.7 1.4 versicolor
6.4 3.2 4.5 1.5 versicolor
6.9 3.1 4.9 1.5 versicolor
5.5 2.3 4.0 1.3 versicolor
6.5 2.8 4.6 1.5 versicolor
5.7 2.8 4.5 1.3 versicolor
6.3 3.3 4.7 1.6 versicolor
4.9 2.4 3.3 1.0 versicolor
6.6 2.9 4.6 1.3 versicolor
5.2 2.7 3.9 1.4 versicolor
5.0 2.0 3.5 1.0 versicolor
5.9 3.0 4.2 1.5 versicolor
6.0 2.2 4.0 1.0 versicolor
6.1 2.9 4.7 1.4 versicolor
5.6 2.9 3.6 1.3 versicolor
6.7 3.1 4.4 1.4 versicolor
5.6 3.0 4.5 1.5 versicolor
5.8 2.7 4.1 1.0 versicolor
6.2 2.2 4.5 1.5 versicolor
5.6 2.5 3.9 1.1 versicolor
5.9 3.2 4.8 1.8 versicolor
6.1 2.8 4.0 1.3 versicolor
6.3 2.5 4.9 1.5 versicolor
6.1 2.8 4.7 1.2 versicolor
6.4 2.9 4.3 1.3 versicolor
6.6 3.0 4.4 1.4 versicolor
6.8 2.8 4.8 1.4 versicolor
6.7 3.0 5.0 1.7 versicolor
6.0 2.9 4.5 1.5 versicolor
5.7 2.6 3.5 1.0 versicolor
5.5 2.4 3.8 1.1 versicolor
5.5 2.4 3.7 1.0 versicolor
5.8 2.7 3.9 1.2 versicolor
6.0 2.7 5.1 1.6 versicolor
5.4 3.0 4.5 1.5 versicolor
6.0 3.4 4.5 1.6 versicolor
6.7 3.1 4.7 1.5 versicolor
6.3 2.3 4.4 1.3 versicolor
5.6 3.0 4.1 1.3 versicolor
5.5 2.5 4.0 1.3 versicolor
5.5 2.6 4.4 1.2 versicolor
6.1 3.0 4.6 1.4 versicolor
5.8 2.6 4.0 1.2 versicolor
5.0 2.3 3.3 1.0 versicolor
5.6 2.7 4.2 1.3 versicolor
5.7 3.0 4.2 1.2 versicolor
5.7 2.9 4.2 1.3 versicolor
6.2 2.9 4.3 1.3 versicolor
5.1 2.5 3.0 1.1 versicolor
5.7 2.8 4.1 1.3 versicolor
6.3 3.3 6.0 2.5 virginica
5.8 2.7 5.1 1.9 virginica
7.1 3.0 5.9 2.1 virginica
6.3 2.9 5.6 1.8 virginica
6.5 3.0 5.8 2.2 virginica
7.6 3.0 6.6 2.1 virginica
4.9 2.5 4.5 1.7 virginica
7.3 2.9 6.3 1.8 virginica
6.7 2.5 5.8 1.8 virginica
7.2 3.6 6.1 2.5 virginica
6.5 3.2 5.1 2.0 virginica
6.4 2.7 5.3 1.9 virginica
6.8 3.0 5.5 2.1 virginica
5.7 2.5 5.0 2.0 virginica
5.8 2.8 5.1 2.4 virginica
6.4 3.2 5.3 2.3 virginica
6.5 3.0 5.5 1.8 virginica
7.7 3.8 6.7 2.2 virginica
7.7 2.6 6.9 2.3 virginica
6.0 2.2 5.0 1.5 virginica
6.9 3.2 5.7 2.3 virginica
5.6 2.8 4.9 2.0 virginica
7.7 2.8 6.7 2.0 virginica
6.3 2.7 4.9 1.8 virginica
6.7 3.3 5.7 2.1 virginica
7.2 3.2 6.0 1.8 virginica
6.2 2.8 4.8 1.8 virginica
6.1 3.0 4.9 1.8 virginica
6.4 2.8 5.6 2.1 virginica
7.2 3.0 5.8 1.6 virginica
7.4 2.8 6.1 1.9 virginica
7.9 3.8 6.4 2.0 virginica
6.4 2.8 5.6 2.2 virginica
6.3 2.8 5.1 1.5 virginica
6.1 2.6 5.6 1.4 virginica
7.7 3.0 6.1 2.3 virginica
6.3 3.4 5.6 2.4 virginica
6.4 3.1 5.5 1.8 virginica
6.0 3.0 4.8 1.8 virginica
6.9 3.1 5.4 2.1 virginica
6.7 3.1 5.6 2.4 virginica
6.9 3.1 5.1 2.3 virginica
5.8 2.7 5.1 1.9 virginica
6.8 3.2 5.9 2.3 virginica
6.7 3.3 5.7 2.5 virginica
6.7 3.0 5.2 2.3 virginica
6.3 2.5 5.0 1.9 virginica
6.5 3.0 5.2 2.0 virginica
6.2 3.4 5.4 2.3 virginica
5.9 3.0 5.1 1.8 virginica

Figure captions with variables

Sometimes we want figure captions to auto-update, e.g. maybe we want them to provide some parameter values. In that case, we can provide !expr, for example

param_val <- 17
```{r}
#| fig-cap: !expr glue::glue("Iris petals multiplied by {param_val}")

ggplot(iris, aes(x = Petal.Length * param_val, y = Petal.Width * param_val, color = Species)) + geom_point()
```

Iris petals multiplied by 17

That’s a bit annoying that we have to build the whole cap as an R expression, but we should be able to use glue, paste, or whatever syntax (will need to sort something out for math and greek, maybe expression or bquote? latex2exp isn’t just working out of the box).

```{r}
#| fig-cap: !expr latex2exp::TeX("$\\alpha$")

ggplot(iris, aes(x = Petal.Length * param_val, y = Petal.Width * param_val, color = Species)) + geom_point()
```

alpha

Website

Starting and updating quarto websites has a few tricks, written up in more detail at those links.

Rendering 1

The error

Error: The process cannot access the file because it is being used by another process. (os error 32),

Seems to be due to dropbox or onedrive even when they are not connected to the folder with the code. Quit them, and it usually goes away. A restart is sometimes required.

Rendering 2

The error

Error in `lazyLoadDBinsertVariable()`: ! long vectors not supported yet: connections.c:6201

is caused by trying to read-in an object too big for a lazy cache. It often only occurs when rendering, not previewing or running the qmd. The solution is to put cache-lazy: false in the chunk header of the offending chunk. Make it go slower, but it goes.